Evaluating Aerosol Optical Depth From Himawari‐8 With Sun Photometer Network

Abstract

The Advanced Himawari Imager (AHI), the primary sensor aboard the Japanese Himawari‐8 geostationary satellite, measures regional aerosol observations with high temporal‐spatial resolution. To improve product quality and scientific applications, we performed a comprehensive evaluation of AHI aerosol products (version 1.0). We compared nearly 2 years (15 July 2015 to 31 June 2017) of AHI aerosol optical depth at 500 nm (AOD500) with AODs from the Aerosol Robotic Network (AERONET) and the Maritime Aerosol Network (MAN). Results showed that, over land, AHI retrievals exhibit a large overall bias of −0.062, with an R of 0.78; over ocean, average bias measured 0.036 (0.051 for MAN), with an R of 0.89 (0.95 for MAN). AHI retrievals collocated with AERONET AODs (τA) showed the following expected AHI AOD errors: (−0.66 × τA + 0.02, −0.34 × τA + 0.16) over land and (−0.24 × τA + 0.03, 0.10 × τA + 0.11) over ocean. AHI retrievals with degraded performance correlated to different regions, angles, aerosol types, and surface types, suggesting that the AHI aerosol algorithm can be improved by changing aerosol optical models, using better cloud filters, and combining multiple methods to estimate ground reflectance. Collocated comparisons of AHI‐MODerate‐resolution Imaging Spectroradiometer‐AERONET demonstrate that, over land, AHI daytime AODs clearly improve when retrievals with a large viewing zenith angle and small scattering angle are excluded.

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data

“…The MAIAC estimation error is a function of scattering angle, which was also found in many other AOD products such as MODIS dark target AOD [7] and JMA AHI AOD [35]. There were several sources of uncertainties in retrieval assumptions that could contribute to this scattering angle dependency, such as the aerosol phase function in the aerosol model [7], surface BRDF model [15], their coupling effects [42], insufficient angle sampling [52], and the geometrical dependence of radiance calibration process [53].…”

“…Only those AOD retrievals flagged as '00 retrieval confidence were used. The JMA AOD has been evaluated recently [35][36][37][38][39], which consistently revealed an AOD underestimation (about 0.06). The JMA AOD products were downloaded from the Japan Aerospace Exploration Agency (JAXA) Earth Observation Research Center (http://www.eorc.jaxa.jp/ptree/terms.html).…”

A Spatial-Temporal Resolved Validation of Source Apportionment by Measurements of Ambient VOCs in Central China

“…In recent years, the number of registered motor vehicles have rapidly increased from~1300 thousand in 2012 to >3200 thousand in 2019. With the rapid development of technological industries and the number of automobiles, Wuhan is facing severe haze pollution [20]. Petrochemical industries, such as basic chemicals, optoelectronics, car spraying, and printing, worsen the situation.…”

Estimating leaf nitrogen concentration based on the combination with fluorescence spectrum and first-derivative

“…Leaf biochemical parameters served as the vital indictors for estimating crops' growth status both locally and globally, and have been widely used in many fields. Leaf nitrogen concentration (LNC) is a key parameter of vegetation photosynthetic efficiency and yields, which can be applied for scientific guidance in nitrogen (N) fertilization management [1][2][3]. Hence, fast and accurate estimation of crops' LNC is vital to indirectly understand crops' growth status [4][5][6].…”